Job Description
Job Requirement :
- Have Implemented and Architected solutions on Google Cloud Platform using the components of GCP
- Experience with Apache Beam/Google Dataflow/Apache Spark in creating end to end data pipelines.
- Experience in some of the following : Big Query, Big Table Cloud Storage, Datastore, Spanner, Cloud SQL, Machine Learning.
- Experience programming in Hadoop, python, SQL
- Expertise in at least two of these technologies: Relational Databases, Analytical Databases, NoSQL databases.
- Certified in Google Professional Data Engineer/ Solution Architect is a major Advantage
Skills Required :
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- Design, develop, and deploy scalable ETL/ELT pipelines using PySpark on GCP.
- Utilize GCP services extensively, including BigQuery (data warehousing), Cloud Storage, Dataproc, and Dataflow.
- Optimize PySpark jobs for performance and reliability, and fine-tune BigQuery queries.
- Implement complex transformations and process large volumes of structured/unstructured data using Spark SQL and PySpark
- Build and manage automated workflows using Apache Airflow or Cloud Composer.
- Strong proficiency in Python and SQL is essential
- Proven experience with Google Cloud Platform (GCP) services.
- Relevant certifications on google cloud is an added advantage.
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